On Prem Manual Flexible Model Deployment Xai
This page outlines how to upload a model artifact or surrogate if you have an on-prem deployment of Fiddler and your deployment doesn't give k8s permissions to create model deployment pods dynamically.
📘 Note
Follow this page if you want to upload a model artifact or a surrogate model. For monitoring only models, without artifact uploaded, this is not required.
Permissions
Model surrogate or artifact upload is going to create a model deployment pod dynamically, one per model with all required requirements to run the model.
Fiddler requires permission to perform CRUD operations on k8s resources like deployment and service. If this permission is not provided, then manual provision is required to spin up the required k8s resources.
In addition, Fiddler offers the ability to run pip install
at runtime to install additional dependencies not included in the chosen image. If this permission is not provided for your deployment, please reach out to the Fiddler team with the list of required of dependencies for your model, and we will build an image for you.
Model On-boarding Steps
Call add_artifact with MANUAL deployment type in the DeploymentParams object. The model artifact will be stored, but no deployment pod will be created at this stage. Model validation and feature impact computation will not be performed. Model deployment status will be inactive.
Manually create Model Deployment k8s resources. Please check the next section and follow the instructions to create the required k8s resources.
Call update_model_deployment with the parameter
active=True
. This step will use the model deployment pod previously created, add the model files, validate the model deployment, and compute global feature impact. Model will be active and available for XAI features after this step.
Instructions to Manually Create Model Deployment k8s Resources
Fiddler will provide a script to create service.yaml
and deployment.yaml
files. Customers can review those files and manually apply those on their deployment. A list of environment variable has to be defined in order to run the script.
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